market-sentiment

Market sentiment analysis aggregates fear/greed index, news sentiment, and social media sentiment signals to gauge investor psychology. It helps traders interpret market mood and identify potential bullish or bearish trend directions by correlating these aggregated signals with price action.

Identifying sentiment extremes involves analyzing aggregated social media and news sentiment data alongside the fear/greed index. Spotting these extremes serves as a contrarian indicator, helping traders correlate extreme market psychology with potential price action reversals for risk management.

Yes, you can apply market sentiment analysis across multiple assets and timeframes. Aggregating fear/greed, news, and social signals supports trading and risk management decisions by providing structured guidance tailored to different market contexts and scales.

Yes, market sentiment analysis outputs structured data suitable for vector embedding. Results include specific fields like eval_note, confidence, sentiment_summary, key_factors, and description, ensuring the aggregated sentiment data is formatted for downstream decision-making and embedding.

The best way to use a contrarian indicator from fear and greed data is to aggregate it with news and social sentiment to identify sentiment extremes. Correlating these extremes with price action allows you to spot potential trend reversals and manage trading risks effectively.

You should not rely solely on social sentiment for investment decisions when it lacks correlation with price action or the fear/greed index. Market sentiment analysis works best when aggregating multiple signals to confirm extremes, rather than using isolated social data.